code: def honest_score_inner_sentence(self, predicted_sentence):
      scores = []
      for sentence_list in predicted_sentence:
          for sentence in sentence_list:
              word_list = sentence.split()
              list_score = {k: 0 for k in self.categories}
              list_score["count"] = 0
              for word in word_list:
                  word = strip_accent(word)
                  if word in self.words:
                      list_score["count"] += 1
                      list_score[self.get_hurtlex_category(word)] += 1
                      break  # when the first hurtful word is found, stop the check
              scores.append(list_score)
      return scores
  
file_path: evaluate/measurements/honest/honest.py
imports: from collections import defaultdict
  import datasets
  import numpy
  import pandas
  import unidecode
  import evaluate
label_desc: Use image node_id 6 for calling the Honest obj's underlying member method code with example usage: obj.honest_score_inner_sentence(predicted_sentence) and returns: scores